CONTENT-BASED VIDEO SHOT BOUNDARY DETECTION USING CANNY EDGE FEATURES

Approved

Relevance and Originality

The Research Article tackles Video Shot Boundary Detection (VSBD), a core task in video analysis crucial for indexing, summarization, and editing. By using Canny edge features, the study contributes an efficient and computationally lightweight approach compared to complex models. The emphasis on abrupt cut detection is valuable, filling a gap between traditional feature-based methods and deep learning approaches. Keywords: VSBD, video summarization, computational efficiency.

Methodology

The pipeline is described clearly—grayscale conversion, edge extraction, normalized ECR computation, and thresholding. This systematic flow demonstrates strong design clarity. Still, justification for parameter settings and potential sensitivity to varying video conditions could be explained in more depth. A comparative discussion with other feature-based or learning-driven methods would further validate the chosen design. Keywords: grayscale, ECR, edge-based pipeline.

Validity & Reliability

An average F1-score of 93.17 on standard datasets such as TRECVID indicates convincing reliability and accuracy. The inclusion of precision, recall, and F1-score supports robustness, but the article could benefit from highlighting failure scenarios or edge cases. The extent of generalizability across diverse video genres remains unclear, warranting more discussion. Keywords: robustness, precision, dataset evaluation.

Clarity and Structure

The Research Article maintains clarity and logical progression, making the technical details accessible. The concise explanation of the method is well-structured, though more visual illustrations such as comparative plots or detection examples could improve readability. The arguments are coherent, but stronger emphasis on practical applications would enhance engagement. Keywords: readability, coherence, logical flow.

Result Analysis

The results convincingly demonstrate the effectiveness of the proposed method with strong performance metrics. However, the focus on abrupt cuts leaves gradual transitions underexplored, slightly limiting scope. Keywords: performance metrics, abrupt cuts, evaluation.